Triple
T23061780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mademoiselle Chambon |
E574920
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Aure Atika |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Aure Atika | Statement: [Mademoiselle Chambon, starredActor, Aure Atika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aure Atika Context triple: [Mademoiselle Chambon, starredActor, Aure Atika]
-
A.
Aure Atika
chosen
Aure Atika is a French actress and filmmaker known for her roles in contemporary French cinema and television, as well as her work as a director and screenwriter.
-
B.
Mimi Chakib
Mimi Chakib was a prominent Egyptian film and stage actress known for her strong supporting roles in classic mid-20th-century Arabic cinema.
-
C.
Naidra Ayadi
Naidra Ayadi is a French actress best known for her acclaimed performance in the gritty crime drama film "Polisse," which earned her significant recognition in French cinema.
-
D.
Nahla Ariela Aubry
Nahla Ariela Aubry is the daughter of American actress Halle Berry and Canadian model Gabriel Aubry.
-
E.
Latifa Ouaou
Latifa Ouaou is a film producer best known for her work on animated features such as DreamWorks' "Puss in Boots."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1899ff96081908d89a07a3b1065c8 |
completed | April 29, 2026, 4:31 a.m. |
Created at: April 17, 2026, 3:55 p.m.